1. Field of the Invention
The invention relates to discriminating automatically for sounds characteristic of a detached part moving in the coolant circuit of an operational pressurized water nuclear reactor or the like, and in particular to a system including a neural network arrangement operable to learn a characteristic signature representing a detached part, and thereafter to discern the occurrence of that signature in operational plant background noise.
2. Prior Art
It is possible to detect loose metallic debris moving through a conduit of a reactor cooling system by sensing the sound the debris makes when impacting against the conduit walls. Over time, loose debris can erode conduits or accumulate in places that cause operational problems. If the debris includes particles of nuclear fuel, accumulations can cause localized heating and emission of radiation. Even if the debris is innocuous metal such as a detached steel nut or bolt, there is a possibility that the debris could become lodged to block proper operation of a mechanical system such as a valve, or could impact against an exposed part, with consequential damage and perhaps the detachment of additional debris. The very powerful flow of coolant through the system tends to drive such debris along with considerable momentum, and it is desirable to monitor for the existence of loose debris such that appropriate corrective action can be taken.
A system for detecting loose debris can be provided by operatively arranging an acoustic sensor, amplifier and threshold detector to monitor the sounds emitted by members of the coolant conduit, especially at angles in the flow path where the momentum of the heavier metallic debris items tends to impel the debris against the conduit wall, or against an obstruction. Such a system would rely on increased amplitude of acoustic emission anywhere within the frequency response range of the sensor and amplifier, and thus could not distinguish between loose parts noises and operational noises such as the background noise of the conduit system in normal operation. Background noises such as the hum of turbulent flow, creaking or snapping noises due to displacement of conduits relative to their supports with thermal expansion, and similar normal noises, cannot readily be distinguished using such a sensing system.
There are known means for improving the discrimination of threshold detection systems. For example, the threshold at which the detector is triggered can be varied to reflect changes in background noise, i.e., triggering only on sounds louder than the present average background level to reduce the instance of erroneous triggering. This has the adverse effect of reducing the likelihood that the noise produced by a loose part will be detected.
A loose part in the coolant flow may produce sounds other than sharp sounds produced by direct .impacts. For example, a loose part may produce a low amplitude sound by scraping along a straight section of conduit, or may affect the sound of the coolant flow by changing the cross section of the conduit at a restriction. Of course, a threshold detection system is unlikely to respond to low amplitude sounds of this kind.